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Listeria detection and surveillance using next generation genomics

Status: 
Past
Competition: 
Application of Genomic Tools to the Detection and Surveillance of Listeria monocytogenes
Sector: 
Health
Agriculture and Agri Food
Genome Centre(s):
Genome Alberta
Project Leader(s):
Linda Chui (University of Alberta), Jian Zhang (Alberta Innovates – Technology Futures), Matthew Gilmour (National Microbiology Laboratory – Public Health Agency of Canada)
Project Description: 

Listeriosis, a serious foodborne illness caused by Listeria bacteria, can be caused by eating contaminated hot dogs, cold cuts, unpasteurized cheese and milk and other foods. Outbreaks have a major impact on public health as well as on the food industry. With current tests, it takes five to 10 days to identify Listeria. This project will lead to the development of a cost-effective and easy-to-perform genetic test that will require much less time to identify the most dangerous strains of Listeria.

Researchers will sequence and map the genomes of many Listeria strains to identify those that are the most harmful and most likely to survive in food processing facilities. They will also develop a database of Listeria genome sequences and identify genetic markers so that harmful Listerias strains in food can be detected rapidly in food processing facilities.

The result will be a test that can be easily used by the food processing industry to screen for the Listeria bacteria that will provide increased food safety for Canadians. Other funding partners for this project include the Canadian Food Inspection Agency (CFIA) and Alberta Innovates Bio-Solutions (AI-Bio).